{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "irish-colombia",
   "metadata": {},
   "source": [
    "# Model building"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "civic-isaac",
   "metadata": {},
   "outputs": [],
   "source": [
    "# importing libraries\n",
    "import sys\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import sklearn.metrics as metrics\n",
    "from joblib import dump\n",
    "from sklearn import tree\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import (\n",
    "    ConfusionMatrixDisplay,\n",
    "    accuracy_score,\n",
    "    auc,\n",
    "    confusion_matrix,\n",
    "    f1_score,\n",
    "    plot_confusion_matrix,\n",
    "    precision_score,\n",
    "    recall_score,\n",
    "    roc_curve,\n",
    ")\n",
    "from sklearn.model_selection import learning_curve, train_test_split\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from xgboost import XGBClassifier, plot_importance\n",
    "\n",
    "sys.path.append(\"../src/\")\n",
    "# from utils import model_eval, plot_learning_curve\n",
    "from tools import model_eval, plot_learning_curve\n",
    "\n",
    "# import user-defined functions\n",
    "# from model_eval import model_eval\n",
    "# from plot_learning_curve import plot_learning_curve"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "spread-pricing",
   "metadata": {},
   "source": [
    "## Load train data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "disturbed-chase",
   "metadata": {},
   "outputs": [],
   "source": [
    "# load train data\n",
    "train = pd.read_csv(\"../data/train_reduced.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "statutory-grace",
   "metadata": {},
   "outputs": [],
   "source": [
    "# removing player_id_cat\n",
    "train = train.drop(\"player_id_cat\", axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "deluxe-nightmare",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6808, 11)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# dimensions\n",
    "train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "liquid-shoulder",
   "metadata": {},
   "source": [
    "## Separating features from the target variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "illegal-resolution",
   "metadata": {},
   "outputs": [],
   "source": [
    "# matrix of features\n",
    "X = train.drop(\"no_churn\", axis=1)\n",
    "\n",
    "# target variable vector\n",
    "y = train[\"no_churn\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "given-peeing",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((6808, 10), (6808,))"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# dimensions\n",
    "X.shape, y.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "embedded-program",
   "metadata": {},
   "source": [
    "## Splitting the dataset into training and test sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "emotional-parliament",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>deposit_approved_sum</th>\n",
       "      <th>withdrawal_approved_sum</th>\n",
       "      <th>turnover_cash_sum</th>\n",
       "      <th>winning_cash_sum</th>\n",
       "      <th>result_cash_sum</th>\n",
       "      <th>NGR_sum</th>\n",
       "      <th>bonus_cash_sum</th>\n",
       "      <th>session_sum</th>\n",
       "      <th>female</th>\n",
       "      <th>male</th>\n",
       "      <th>no_churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>87</td>\n",
       "      <td>146</td>\n",
       "      <td>309</td>\n",
       "      <td>337</td>\n",
       "      <td>28</td>\n",
       "      <td>-29</td>\n",
       "      <td>106</td>\n",
       "      <td>81819</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1915</td>\n",
       "      <td>109</td>\n",
       "      <td>5003</td>\n",
       "      <td>3197</td>\n",
       "      <td>-1806</td>\n",
       "      <td>1785</td>\n",
       "      <td>98</td>\n",
       "      <td>28623</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>91</td>\n",
       "      <td>0</td>\n",
       "      <td>280</td>\n",
       "      <td>189</td>\n",
       "      <td>-91</td>\n",
       "      <td>90</td>\n",
       "      <td>0</td>\n",
       "      <td>5468</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>103</td>\n",
       "      <td>45</td>\n",
       "      <td>-58</td>\n",
       "      <td>59</td>\n",
       "      <td>41</td>\n",
       "      <td>2122</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1885</td>\n",
       "      <td>1345</td>\n",
       "      <td>8751</td>\n",
       "      <td>8036</td>\n",
       "      <td>-715</td>\n",
       "      <td>513</td>\n",
       "      <td>69</td>\n",
       "      <td>23072</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   deposit_approved_sum  withdrawal_approved_sum  turnover_cash_sum  \\\n",
       "0                    87                      146                309   \n",
       "1                  1915                      109               5003   \n",
       "2                    91                        0                280   \n",
       "3                    59                        0                103   \n",
       "4                  1885                     1345               8751   \n",
       "\n",
       "   winning_cash_sum  result_cash_sum  NGR_sum  bonus_cash_sum  session_sum  \\\n",
       "0               337               28      -29             106        81819   \n",
       "1              3197            -1806     1785              98        28623   \n",
       "2               189              -91       90               0         5468   \n",
       "3                45              -58       59              41         2122   \n",
       "4              8036             -715      513              69        23072   \n",
       "\n",
       "   female  male  no_churn  \n",
       "0     1.0   0.0         1  \n",
       "1     0.0   1.0         1  \n",
       "2     0.0   1.0         1  \n",
       "3     1.0   0.0         1  \n",
       "4     0.0   1.0         1  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "favorite-congo",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "oriented-milton",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train features shape :  (5446, 10)\n",
      "Train target shape   :  (5446,)\n",
      "Test features shape  :  (1362, 10)\n",
      "Test target shape    :  (1362,)\n"
     ]
    }
   ],
   "source": [
    "# splitting dataset into training and test sets\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    X, y, test_size=0.2, random_state=42\n",
    ")\n",
    "\n",
    "print(\"Train features shape : \", X_train.shape)\n",
    "print(\"Train target shape   : \", y_train.shape)\n",
    "print(\"Test features shape  : \", X_test.shape)\n",
    "print(\"Test target shape    : \", y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "juvenile-zoning",
   "metadata": {},
   "source": [
    "## Model selection\n",
    "\n",
    "After defining our target variable using the probabilities obtained from the BG-NBD model, we now can perform some experimentation to search for a model that allows us to predict the churn problem.\n",
    "\n",
    "In the present model we remove all the features obtained with the model BG-NBD: `frequency`, `recency`, `T` (age), `monetary_value` and `purchase_next_4_weeks`."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "discrete-fleet",
   "metadata": {},
   "source": [
    "To tackle the churn problem for the `casino_classic` gamblers, that constitutes 71.3% of our dataset, we'll compare the performance for the following classification algorithms:\n",
    "* Decision Tree\n",
    "* k-Nearest Neighbors\n",
    "* Logistic Regression\n",
    "* Random Forest\n",
    "* XGBoost"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "sought-ridge",
   "metadata": {},
   "source": [
    "We should also remember at this point that we have an imbalanced dataset with:\n",
    "* around 80% of users in the positive class (will not churn)\n",
    "* around 20% of users in the negative class (will churn)\n",
    "\n",
    "For this task, we'll first choose a model based on its performance using default parameters to establish a baseline. After evaluating the model, we'll decide on the need for more advanced techniques to handle the class imbalance (under- or over-sampling) or to perform hyperparameter tunning, for example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "liked-radiation",
   "metadata": {},
   "outputs": [],
   "source": [
    "# define a list of models and of model names\n",
    "models = [\n",
    "    LogisticRegression(n_jobs=-1, random_state=42),\n",
    "    KNeighborsClassifier(n_jobs=-1),\n",
    "    DecisionTreeClassifier(max_depth=10, random_state=42),\n",
    "    RandomForestClassifier(random_state=42, n_jobs=-1),\n",
    "    XGBClassifier(random_state=42, use_label_encoder=False, n_jobs=-1),\n",
    "]\n",
    "\n",
    "model_names = [\n",
    "    \"Logistic Regression\",\n",
    "    \"k-Nearest Neighbors\",\n",
    "    \"Decision Tree\",\n",
    "    \"Random Forest\",\n",
    "    \"XGBoost\",\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "assigned-member",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[15:45:04] WARNING: ../src/learner.cc:1061: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    }
   ],
   "source": [
    "# train and evaluate models\n",
    "acc = []\n",
    "f1 = []\n",
    "precision = []\n",
    "recall = []\n",
    "\n",
    "eval_acc = {}\n",
    "eval_f1 = {}\n",
    "eval_precision = {}\n",
    "eval_recall = {}\n",
    "\n",
    "for model in range(len(models)):\n",
    "    classification_model = models[model]\n",
    "    classification_model.fit(X_train, y_train)\n",
    "    y_pred = classification_model.predict(X_test)\n",
    "\n",
    "    acc.append(accuracy_score(y_test, y_pred))\n",
    "    f1.append(f1_score(y_test, y_pred))\n",
    "    precision.append(precision_score(y_test, y_pred))\n",
    "    recall.append(recall_score(y_test, y_pred))\n",
    "\n",
    "eval_acc = {\"Modeling Algorithm\": model_names, \"Accuracy\": acc}\n",
    "eval_f1 = {\"Modeling Algorithm\": model_names, \"F1 score\": f1}\n",
    "eval_precision = {\"Modeling Algorithm\": model_names, \"Precision\": precision}\n",
    "eval_recall = {\"Modeling Algorithm\": model_names, \"Recall\": recall}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "novel-merit",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Modeling Algorithm</th>\n",
       "      <th>Accuracy</th>\n",
       "      <th>F1 score</th>\n",
       "      <th>Precision</th>\n",
       "      <th>Recall</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Random Forest</td>\n",
       "      <td>0.773862</td>\n",
       "      <td>0.868376</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>0.949533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>XGBoost</td>\n",
       "      <td>0.763583</td>\n",
       "      <td>0.859634</td>\n",
       "      <td>0.805556</td>\n",
       "      <td>0.921495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Decision Tree</td>\n",
       "      <td>0.756241</td>\n",
       "      <td>0.855022</td>\n",
       "      <td>0.802459</td>\n",
       "      <td>0.914953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>k-Nearest Neighbors</td>\n",
       "      <td>0.756241</td>\n",
       "      <td>0.854514</td>\n",
       "      <td>0.804455</td>\n",
       "      <td>0.911215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Logistic Regression</td>\n",
       "      <td>0.668869</td>\n",
       "      <td>0.791493</td>\n",
       "      <td>0.783166</td>\n",
       "      <td>0.800000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Modeling Algorithm  Accuracy  F1 score  Precision    Recall\n",
       "3        Random Forest  0.773862  0.868376   0.800000  0.949533\n",
       "4              XGBoost  0.763583  0.859634   0.805556  0.921495\n",
       "2        Decision Tree  0.756241  0.855022   0.802459  0.914953\n",
       "1  k-Nearest Neighbors  0.756241  0.854514   0.804455  0.911215\n",
       "0  Logistic Regression  0.668869  0.791493   0.783166  0.800000"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a table containing the performance of each model\n",
    "df_acc = pd.DataFrame(eval_acc)\n",
    "df_f1 = pd.DataFrame(eval_f1)\n",
    "df_precision = pd.DataFrame(eval_precision)\n",
    "df_recall = pd.DataFrame(eval_recall)\n",
    "\n",
    "score_table = pd.concat(\n",
    "    [df_acc, df_f1[\"F1 score\"], df_precision[\"Precision\"], df_recall[\"Recall\"]], axis=1\n",
    ")\n",
    "score_table.sort_values(by=\"F1 score\", ascending=[False])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "objective-tennis",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot model performances according to 4 traditional metrics\n",
    "plt.style.use(\"fivethirtyeight\")\n",
    "ax = score_table.sort_values(by=[\"F1 score\"]).plot(\n",
    "    kind=\"barh\", x=\"Modeling Algorithm\", figsize=(10, 6), stacked=False\n",
    ")\n",
    "ax.legend(bbox_to_anchor=(1, 1.17))\n",
    "plt.grid(which=\"minor\", axis=\"x\", color=\"k\")\n",
    "plt.show()\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "crazy-wheat",
   "metadata": {},
   "source": [
    "Using default parameters all of our models had apparently a pretty good performance, and as we can see from the previous plot, the best performances were obtained by:\n",
    "* Random Forest\n",
    "* XGBoost\n",
    "* k-Nearest Neighbors\n",
    "\n",
    "Since we have an imbalanced dataset, accuracy is not the recommended metric to be used. In this case, it's better to use:\n",
    "* precision (out of those which I classiﬁed as positives correctly predicted, how many are correct?) \n",
    "* recall (out of all positives, how many did I find?), \n",
    "* or F1 score (balances precision and recall in a single number). Suited for the imbalanced class problem, but less explainable.\n",
    "\n",
    "\n",
    "|Metrics (T = true, F = false, P = positive, N = negative)                                      |\n",
    "|:----------------------------------------------------------------------------------------------|\n",
    "| \\begin{align} Accuracy = \\frac{TP+TN}{TP+TN+FN+FP} \\end{align}                                |\n",
    "| \\begin{align} Recall = \\frac{TP}{TP+FN} \\end{align}                                           |\n",
    "| \\begin{align} Precision = \\frac{TP}{TP+FP} \\end{align}                                        |\n",
    "| \\begin{align} F1= \\frac{2 \\cdot Precision \\cdot Recall}{Precision+Recall} \\end{align}         |\n",
    "\n",
    "\n",
    "From our three best performers, the Random Forest will be our choice. From the results we can confirm that accuracy is not the best choice for our problem."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "vertical-project",
   "metadata": {},
   "source": [
    "## Random Forest"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "tired-outreach",
   "metadata": {},
   "source": [
    "### Model with default parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "other-newton",
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a classifier\n",
    "rf_model_default = RandomForestClassifier(random_state=42, n_jobs=-1)\n",
    "# train the model\n",
    "rf_model_default.fit(X_train, y_train)\n",
    "# predictions\n",
    "y_pred = rf_model_default.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "extraordinary-blanket",
   "metadata": {},
   "source": [
    "#### Metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "threaded-argentina",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1 score:  0.8684\n",
      "Precision: 0.8\n",
      "Recall:    0.9495\n",
      "Accuracy:  0.7739\n"
     ]
    }
   ],
   "source": [
    "# model evaluation\n",
    "model_eval(y_test, y_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "typical-shaft",
   "metadata": {},
   "source": [
    "#### Confusion matrix\n",
    "\n",
    "Calculating the confusion matrix helps us to summarize the performance of our model. The convention used by scikit learn is given below."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "spoken-equilibrium",
   "metadata": {},
   "source": [
    "|  Scikit learn convention   |\n",
    "|:-----:|\n",
    "|TN FP|\n",
    "|FN TP|"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "sound-matrix",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# define class names\n",
    "class_names = [\"churn\", \" no_churn\"]\n",
    "\n",
    "# build the confusion matrix\n",
    "confusion = confusion_matrix(y_test, y_pred)\n",
    "# print(f\"Confusion matrix:\\n{confusion}\")\n",
    "\n",
    "# display the confusion matrix\n",
    "ConfusionMatrixDisplay(confusion, display_labels=class_names).plot()\n",
    "plt.show()\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "vertical-monster",
   "metadata": {},
   "source": [
    "The above confusion matrix summarizes the correct and incorrect predictions made by our model. The amount of predicted false positives (top right) and false negatives (top left) increased comparing with the model that keep the features from the BG-NBD model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "working-jersey",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # calculate the ROC curve\n",
    "probs = rf_model_default.predict_proba(X_test)\n",
    "preds = probs[:, 1]\n",
    "fpr_rf, tpr_rf, _ = metrics.roc_curve(y_test, preds)\n",
    "roc_auc_rf = metrics.auc(fpr_rf, tpr_rf)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "secure-mainstream",
   "metadata": {},
   "source": [
    "#### Save the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "demanding-alliance",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['../models/rf_tree_model_default.joblib']"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# save the model\n",
    "dump(rf_model_default, \"../models/rf_tree_model_default.joblib\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "apparent-looking",
   "metadata": {},
   "source": [
    "# Decision Tree\n",
    "\n",
    "For the sake of comparison with the model with more features let's see how the decision tree performs here."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "flying-mention",
   "metadata": {},
   "source": [
    "#### Model with default parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "promising-logan",
   "metadata": {},
   "outputs": [],
   "source": [
    "# create a classifier\n",
    "tree_model_reduced = DecisionTreeClassifier(max_depth=3, class_weight='balanced', criterion='gini', random_state=42)\n",
    "# train the model\n",
    "tree_model_reduced.fit(X_train, y_train)\n",
    "# predictions\n",
    "y_pred = tree_model_reduced.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "atlantic-government",
   "metadata": {},
   "source": [
    "#### Metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "rough-novel",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1 score:  0.6807\n",
      "Precision: 0.9067\n",
      "Recall:    0.5449\n",
      "Accuracy:  0.5984\n"
     ]
    }
   ],
   "source": [
    "# model evaluation\n",
    "model_eval(y_test, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "disciplinary-borough",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# define class names\n",
    "class_names = [\"churn\", \" no churn\"]\n",
    "\n",
    "# build the confusion matrix\n",
    "confusion = confusion_matrix(y_test, y_pred)\n",
    "# print(f\"Confusion matrix:\\n{confusion}\")\n",
    "\n",
    "# display the confusion matrix\n",
    "ConfusionMatrixDisplay(confusion, display_labels=class_names).plot()\n",
    "plt.show()\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "established-millennium",
   "metadata": {},
   "source": [
    "Using decision tree with `max_depth=5` decreased the number false negatives, while slightly increasing the number of false positives. It can be further improve with hyperparameter tunning."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "worse-baker",
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_names = [\n",
    "    \"deposit_approved_sum\",\n",
    "    \"withdrawal_approved_sum\",\n",
    "    \"turnover_cash_sum\",\n",
    "    \"winning_cash_sum\",\n",
    "    \"result_cash_sum\",\n",
    "    \"NGR_sum\",\n",
    "    \"bonus_cash_sum\",\n",
    "    \"session_sum\",\n",
    "    \"female\",\n",
    "    \"male\",\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "searching-northwest",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1296 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize our tree\n",
    "fig = plt.figure(figsize=(20, 18))\n",
    "_ = tree.plot_tree(\n",
    "    tree_model_reduced,\n",
    "    max_depth=3,\n",
    "    feature_names=feature_names,\n",
    "    class_names=class_names,\n",
    "    proportion=True,\n",
    "    filled=True,\n",
    "    rounded=True,\n",
    "    fontsize=11,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "efficient-jerusalem",
   "metadata": {},
   "source": [
    "For the sake of clarity, the tree plot above is shown with `max_depth=3`, but the model was build `max_depth=5`.\n",
    "\n",
    "Now we have a completely different model, that is more suitable to be used with the original dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "unlimited-citation",
   "metadata": {},
   "source": [
    "#### Learning curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "humanitarian-asbestos",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 8))\n",
    "plot_learning_curve(X, y, 5, plt)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "preceding-nebraska",
   "metadata": {},
   "source": [
    "## Comparing ROCs: Random Forest and Decision Tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "normal-tomorrow",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# calculate the ROC curve\n",
    "probs = tree_model_reduced.predict_proba(X_test)\n",
    "preds = probs[:, 1]\n",
    "fpr, tpr, _ = metrics.roc_curve(y_test, preds)\n",
    "roc_auc = metrics.auc(fpr, tpr)\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.title(\"Receiver Operating Characteristic (ROC)\", size=20)\n",
    "plt.plot(fpr, tpr, \"bo-\", label=\"AUC DT = %0.2f\" % roc_auc)\n",
    "plt.plot(fpr_rf, tpr_rf, \"go-\", label=\"AUC RF = %0.2f\" % roc_auc_rf)\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.plot([0, 1], [0, 1], \"r--\")\n",
    "plt.xlim([-0.1, 1.1])\n",
    "plt.ylim([-0.1, 1.1])\n",
    "plt.ylabel(\"True Positive Rate (Sensitivity)\", size=18)\n",
    "plt.xlabel(\"False Positive Rate (1 - Specificity)\", size=18)\n",
    "plt.show()\n",
    "plt.close()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
